Cobain GIC

Overview:

This page contains the results of CoNGA analyses. Results in tables may have been filtered to reduce redundancy, focus on the most important columns, and limit length; full tables should exist as OUTFILE_PREFIX*.tsv files.

Command:

scripts/run_conga.py --all --gex_data /scratch.global/ben_testing/ben_tcr/Rotelle_GIC/outs/filtered_feature_bc_matrix.h5 --gex_data_type 10x_h5 --clones_file Rotelle_GIC_TCR --organism human --outfile_prefix Rotelle_GIC_Final2

Stats

num_cells_w_gex: 14913
num_features_start: 26530
num_cells_w_tcr: 733
min_genes_per_cell: 200
max_genes_per_cell: 3500
max_percent_mito: 0.1
num_filt_max_genes_per_cell: 91
num_filt_max_percent_mito: 0
num_antibody_features: 0
num_TR_genes: 43
num_TR_genes_in_hvg_set: 42
num_highly_variable_genes: 1670
num_cells_after_filtering: 642
num_clonotypes: 532
max_clonotype_size: 16
num_singleton_clonotypes: 467
nbr_frac_for_nndists: 0.1
num_gvg_hit_clonotypes: 11
num_gvg_hit_biclusters: 0

graph_vs_graph_stats

Here we are assessing overall graph-vs-graph correlation by looking at the shared edges between TCR and GEX neighbor graphs and comparing that observed number to the number we would expect if the graphs were completely uncorrelated. Our null model for uncorrelated graphs is to take the vertices of one graph and randomly renumber them (permute their labels). We compare the observed overlap to that expected under this null model by computing a Z-score, either by permuting one of the graph's vertices many times to get a mean and standard deviation of the overlap distribution, or, for large graphs where this is time consuming, by using a regression model for the standard deviation. The different rows of this table correspond to the different graph-graph comparisons that we make in the conga graph-vs-graph analysis: we compare K-nearest-neighbor graphs for GEX and TCR at different K values ("nbr_frac" aka neighbor-fraction, which reports K as a fraction of the total number of clonotypes) to each other and to GEX and TCR "cluster" graphs in which each clonotype is connected to all the other clonotypes with the same (GEX or TCR) cluster assignment. For two K values (the default), this gives 2*3=6 comparisons: GEX KNN graph vs TCR KNN graph, GEX cluster graph vs TCR KNN graph, and GEX KNN graph vs TCR cluster graph, for each of the two K values (aka nbr_fracs).

The column to look at is *overlap_zscore*. Higher values indicate more significant GEX/TCR covariation, with "interesting" levels starting around zscores of 3-5.

Columns in more detail:

graph_overlap_type: KNN ("nbr") or cluster versus KNN ("nbr") or cluster

nbr_frac: the K value for the KNN graph, as a fraction of total clonotypes

overlap: the observed overlap (number of shared edges) between GEX and TCR graphs

expected_overlap: the expected overlap under a shuffled null model.

overlap_zscore: a Z-score for the observed overlap computed by subtracting the expected overlap and dividing by the standard deviation estimated from shuffling.

overlap	expected_overlap	overlap_mean	overlap_sdev	overlap_zscore	overlap_zscore_fitted	overlap_zscore_source	nodes	calculation_time	calculation_time_fitted	gex_edges	tcr_edges	gex_indegree_variance	gex_indegree_skewness	gex_indegree_kurtosis	tcr_indegree_variance	tcr_indegree_skewness	tcr_indegree_kurtosis	indegree_correlation_R	indegree_correlation_P	nbr_frac	graph_overlap_type
41	25.047081	25.71	6.255070	2.444417	4.397082	shuffling	532	0.059355	0.001543	2660	2660	1.414689	2.431343	9.051368	0.383277	0.932702	0.989053	0.066905	0.123253	0.01	gex_nbr_vs_tcr_nbr
289	261.920904	259.89	17.754940	1.639544	1.748683	shuffling	532	0.216329	0.017912	2660	27816	1.414689	2.431343	9.051368	0.194624	0.616989	-0.808238	0.029297	0.500129	0.01	gex_nbr_vs_tcr_cluster
470	402.749529	403.14	22.576988	2.961422	5.014587	shuffling	532	0.317310	0.028074	42772	2660	0.125965	-0.635407	-0.830691	0.383277	0.932702	0.989053	0.036501	0.400791	0.01	gex_cluster_vs_tcr_nbr
3043	2814.290019	2809.03	85.511924	2.736110	2.820836	shuffling	532	0.251573	0.174766	28196	28196	1.126519	1.580659	2.593195	0.258051	1.777979	6.075861	0.064742	0.135874	0.10	gex_nbr_vs_tcr_nbr
2846	2776.361582	2786.90	83.231545	0.710067	0.931263	shuffling	532	0.256546	0.172307	28196	27816	1.126519	1.580659	2.593195	0.194624	0.616989	-0.808238	0.036406	0.402021	0.10	gex_nbr_vs_tcr_cluster
4440	4269.145009	4268.83	77.180186	2.217797	2.752895	shuffling	532	0.446019	0.270063	42772	28196	0.125965	-0.635407	-0.830691	0.258051	1.777979	6.075861	-0.033397	0.442066	0.10	gex_cluster_vs_tcr_nbr

graph_vs_graph

Graph vs graph analysis looks for correlation between GEX and TCR space by finding statistically significant overlap between two similarity graphs, one defined by GEX similarity and one by TCR sequence similarity.

Overlap is defined one node (clonotype) at a time by looking for overlap between that node's neighbors in the GEX graph and its neighbors in the TCR graph. The null model is that the two neighbor sets are chosen independently at random.

CoNGA looks at two kinds of graphs: K nearest neighbor (KNN) graphs, where K = neighborhood size is specified as a fraction of the number of clonotypes (defaults for K are 0.01 and 0.1), and cluster graphs, where each clonotype is connected to all the other clonotypes in the same (GEX or TCR) cluster. Overlaps are computed 3 ways (GEX KNN vs TCR KNN, GEX KNN vs TCR cluster, and GEX cluster vs TCR KNN), for each of the K values (called nbr_fracs short for neighbor fractions).

Columns (depend slightly on whether hit is KNN v KNN or KNN v cluster): conga_score = P value for GEX/TCR overlap * number of clonotypes mait_fraction = fraction of the overlap made up of 'invariant' T cells num_neighbors* = size of neighborhood (K) cluster_size = size of cluster (for KNN v cluster graph overlaps) clone_index = 0-index of clonotype in adata object

conga_score	num_neighbors_gex	num_neighbors_tcr	overlap	overlap_corrected	mait_fraction	clone_index	nbr_frac	graph_overlap_type	cluster_size	gex_cluster	tcr_cluster	va	ja	cdr3a	vb	jb	cdr3b
0.120163	53.0	53.0	14	14	0.0	112	0.10	gex_nbr_vs_tcr_nbr	NaN	1	0	TRAV13-2*01	TRAJ45*01	CAETGGSANRLTF	TRBV27*01	TRBJ2-7*01	CASSFARTQYEQYF
0.134907	NaN	5.0	5	5	0.0	422	0.01	gex_cluster_vs_tcr_nbr	103.0	1	7	TRAV6*01	TRAJ37*01	CAPVSNTGKLIF	TRBV7-2*01	TRBJ1-4*01	CASSLPGGLGEKLFF
0.373793	5.0	5.0	2	2	0.0	34	0.01	gex_nbr_vs_tcr_nbr	NaN	7	0	TRAV12-1*01	TRAJ33*01	CAVRLDSNYQLIW	TRBV3-2*01	TRBJ2-1*01	CASRAAGGSNEQFF
0.373793	5.0	5.0	2	2	0.0	225	0.01	gex_nbr_vs_tcr_nbr	NaN	5	5	TRAV20*01	TRAJ11*01	CAVPRDGTLTF	TRBV5-7*01	TRBJ2-4*01	CASSFWTGEQNTQYF
0.378032	5.0	5.0	2	2	1.0	14	0.01	gex_nbr_vs_tcr_nbr	NaN	4	9	TRAV1-2*01	TRAJ33*01	CAVRDSNYQLIW	TRBV10-1*01	TRBJ2-6*01	CASSEEGGSGASVLTF
0.378032	5.0	5.0	2	2	1.0	16	0.01	gex_nbr_vs_tcr_nbr	NaN	4	9	TRAV1-2*01	TRAJ33*01	CAVRDSNYQLIW	TRBV4-3*01	TRBJ2-6*01	CASSQEGGGASVLTF
0.417430	NaN	53.0	14	14	0.0	35	0.10	gex_cluster_vs_tcr_nbr	59.0	4	10	TRAV12-1*01	TRAJ34*01	CAVRPRHNANKLIF	TRBV7-2*01	TRBJ2-2*01	CASSQQRLGGLANTAQLFF
0.556993	NaN	53.0	9	9	0.0	434	0.10	gex_cluster_vs_tcr_nbr	29.0	6	1	TRAV8-2*01	TRAJ27*01	CAVNDMRADKLTF	TRBV13*01	TRBJ2-5*01	CASSSSAEKGTQYF
0.696650	53.0	NaN	7	7	0.0	271	0.10	gex_nbr_vs_tcr_cluster	19.0	3	11	TRAV21*01	TRAJ47*01	CAVRPDYGNKLIF	TRBV13*01	TRBJ2-3*01	CASSPLPATDPQYF
0.696650	53.0	NaN	7	7	0.0	283	0.10	gex_nbr_vs_tcr_cluster	19.0	3	11	TRAV24*01	TRAJ9*01	CAFGTGGFKTVF	TRBV15*01	TRBJ1-5*01	CASSKQTGGSNQPQYF
0.726670	NaN	5.0	3	3	0.0	434	0.01	gex_cluster_vs_tcr_nbr	29.0	6	1	TRAV8-2*01	TRAJ27*01	CAVNDMRADKLTF	TRBV13*01	TRBJ2-5*01	CASSSSAEKGTQYF
0.802195	NaN	53.0	16	16	0.0	425	0.10	gex_cluster_vs_tcr_nbr	77.0	3	7	TRAV6*01	TRAJ41*01	CAAEDSGYALNF	TRBV5-8*01	TRBJ2-1*01	CASSWIGTGGSTEQFF

tcr_clumping

This table stores the results of the TCR "clumping" analysis, which looks for neighborhoods in TCR space with more TCRs than expected by chance under a simple null model of VDJ rearrangement.

For each TCR in the dataset, we count how many TCRs are within a set of fixed TCRdist radii (defaults: 24,48,72,96), and compare that number to the expected number given the size of the dataset using the poisson model. Inspired by the ALICE and TCRnet methods.

Columns: clump_type='global' unless we are optionally looking for TCR clumps within the individual GEX clusters num_nbrs = neighborhood size (number of other TCRs with TCRdist

clump_type	clone_index	nbr_radius	pvalue_adj	num_nbrs	expected_num_nbrs	raw_count	va	ja	cdr3a	vb	jb	cdr3b	clonotype_fdr_value	clumping_group	clusters_gex	clusters_tcr
global	87	48	0.000119	2	0.000334	1572.0	TRAV13-1*01	TRAJ36*01	CAAKDEVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASKDGYEQYF	0.000118	1	3	0
global	89	48	0.000328	2	0.000555	2615.0	TRAV13-1*01	TRAJ36*01	CAAKDGVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASTEAYEQYF	0.000118	1	2	0
global	88	48	0.000355	2	0.000578	2721.0	TRAV13-1*01	TRAJ36*01	CAAKDGVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASTLGYEQYF	0.000118	1	2	0
global	183	48	0.003560	2	0.001830	8617.0	TRAV19*01	TRAJ39*01	CALNERNNAGNVLTF	TRBV6-3*01	TRBJ2-3*01	CASSYSRGLSDPQYF	0.000890	2	2	2
global	239	96	0.011321	3	0.031976	150545.0	TRAV20*01	TRAJ43*01	CAHNDIRF	TRBV9*01	TRBJ2-1*01	CASSLWGELNEQFF	0.002127	3	2	5
global	515	24	0.013108	1	0.000006	29.0	TRAV9-2*01	TRAJ36*01	CALTQTGVNNLFF	TRBV20-1*01	TRBJ1-2*01	CSARDPRRTDYTF	0.002127	6	4	3
global	87	72	0.014886	2	0.003745	17632.0	TRAV13-1*01	TRAJ36*01	CAAKDEVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASKDGYEQYF	0.000118	1	3	0
global	89	72	0.025253	2	0.004880	22974.0	TRAV13-1*01	TRAJ36*01	CAAKDGVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASTEAYEQYF	0.000118	1	2	0
global	88	72	0.028254	2	0.005162	24303.0	TRAV13-1*01	TRAJ36*01	CAAKDGVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASTLGYEQYF	0.000118	1	2	0
global	514	24	0.036611	1	0.000017	81.0	TRAV9-2*01	TRAJ36*01	CALSQTGVNNLFF	TRBV20-1*01	TRBJ1-2*01	CSARDPRATDYTF	0.003661	6	4	3
global	331	96	0.043454	2	0.006404	30152.0	TRAV38-1*01	TRAJ27*01	CAFINTNADKLTF	TRBV13*01	TRBJ2-4*01	CASSLLVGGRENTQYF	0.003950	7	0	11
global	264	24	0.068249	1	0.000032	151.0	TRAV21*01	TRAJ31*01	CAVRNNNDRVIF	TRBV7-6*01	TRBJ1-1*01	CASSFSRNTEAFF	0.005250	4	1	10
global	263	24	0.068249	1	0.000032	151.0	TRAV21*01	TRAJ31*01	CAARNNNDRVIF	TRBV7-6*01	TRBJ1-1*01	CASSFSRNTEAFF	0.005250	4	2	10
global	403	72	0.086964	2	0.009068	42693.0	TRAV6*01	TRAJ23*01	CALAYNQAGKLIF	TRBV6-3*01	TRBJ2-5*01	CASSSLEETQYF	0.006212	5	2	7
global	89	24	0.112542	1	0.000053	249.0	TRAV13-1*01	TRAJ36*01	CAAKDGVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASTEAYEQYF	0.000118	1	2	0
global	88	24	0.120677	1	0.000057	267.0	TRAV13-1*01	TRAJ36*01	CAAKDGVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASTLGYEQYF	0.000118	1	2	0
global	240	96	0.147130	2	0.011806	55582.0	TRAV20*01	TRAJ43*01	CAVPVRF	TRBV9*01	TRBJ1-5*01	CASSPWGEDQPQYF	0.008260	3	3	5
global	183	96	0.148889	3	0.076316	359305.0	TRAV19*01	TRAJ39*01	CALNERNNAGNVLTF	TRBV6-3*01	TRBJ2-3*01	CASSYSRGLSDPQYF	0.000890	2	2	2
global	179	96	0.156943	2	0.012195	57413.0	TRAV19*01	TRAJ39*01	CALNERNNAGNVLTF	TRBV6-8*01	TRBJ2-1*01	CGSSYSRTGANNEQFF	0.008260	2	2	2
global	515	48	0.217395	1	0.000102	481.0	TRAV9-2*01	TRAJ36*01	CALTQTGVNNLFF	TRBV20-1*01	TRBJ1-2*01	CSARDPRRTDYTF	0.002127	6	4	3
global	242	96	0.224534	2	0.014598	68727.0	TRAV20*01	TRAJ43*01	CAVQDIRF	TRBV9*01	TRBJ1-1*01	CASSLWGENTEAFF	0.010692	3	2	5
global	183	72	0.235749	2	0.014960	70431.0	TRAV19*01	TRAJ39*01	CALNERNNAGNVLTF	TRBV6-3*01	TRBJ2-3*01	CASSYSRGLSDPQYF	0.000890	2	2	2
global	391	96	0.352987	2	0.018326	86279.0	TRAV5*01	TRAJ32*01	CAENYGGSGNKLIF	TRBV13*01	TRBJ2-3*01	CASSWLLGGTDPQYF	0.015347	8	3	11
global	183	24	0.397260	1	0.000187	879.0	TRAV19*01	TRAJ39*01	CALNERNNAGNVLTF	TRBV6-3*01	TRBJ2-3*01	CASSYSRGLSDPQYF	0.000890	2	2	2
global	242	48	0.418047	1	0.000196	925.0	TRAV20*01	TRAJ43*01	CAVQDIRF	TRBV9*01	TRBJ1-1*01	CASSLWGENTEAFF	0.010692	3	2	5
global	405	48	0.458266	1	0.000215	1014.0	TRAV6*01	TRAJ23*01	CALSYNQAGKLIF	TRBV6-3*01	TRBJ2-5*01	CASGNLQETQYF	0.017376	5	2	7
global	182	24	0.469145	1	0.000220	1042.0	TRAV19*01	TRAJ39*01	CALNERNNAGNVLTF	TRBV6-3*01	TRBJ2-3*01	CASSYSRGLTDPQYF	0.017376	2	2	2
global	514	48	0.504358	1	0.000237	1116.0	TRAV9-2*01	TRAJ36*01	CALSQTGVNNLFF	TRBV20-1*01	TRBJ1-2*01	CSARDPRATDYTF	0.003661	6	4	3
global	263	48	0.616873	1	0.000290	1365.0	TRAV21*01	TRAJ31*01	CAARNNNDRVIF	TRBV7-6*01	TRBJ1-1*01	CASSFSRNTEAFF	0.005250	4	2	10
global	264	48	0.616873	1	0.000290	1365.0	TRAV21*01	TRAJ31*01	CAVRNNNDRVIF	TRBV7-6*01	TRBJ1-1*01	CASSFSRNTEAFF	0.005250	4	1	10
global	87	96	0.653167	2	0.024984	117625.0	TRAV13-1*01	TRAJ36*01	CAAKDEVNNLFF	TRBV10-1*01	TRBJ2-7*01	CASKDGYEQYF	0.000118	1	3	0
global	405	96	0.793866	2	0.027567	129788.0	TRAV6*01	TRAJ23*01	CALSYNQAGKLIF	TRBV6-3*01	TRBJ2-5*01	CASGNLQETQYF	0.017376	5	2	7

tcr_clumping_logos

This figure summarizes the results of a CoNGA analysis that produces scores (TCR clumping) and clusters. At the top are six 2D UMAP projections of clonotypes in the dataset based on GEX similarity (top left three panels) and TCR similarity (top right three panels), colored from left to right by GEX cluster assignment; TCR clumping score; joint GEX:TCR cluster assignment for clonotypes with significant TCR clumping scores, using a bicolored disk whose left half indicates GEX cluster and whose right half indicates TCR cluster; TCR cluster; TCR clumping; GEX:TCR cluster assignments for TCR clumping hits, as in the third panel.

Below are two rows of GEX landscape plots colored by (first row, left) expression of selected marker genes, (second row, left) Z-score normalized and GEX-neighborhood averaged expression of the same marker genes, and (both rows, right) TCR sequence features (see CoNGA manuscript Table S3 for TCR feature descriptions).

GEX and TCR sequence features of TCR clumping hits in clusters with 3 or more hits are summarized by a series of logo-style visualizations, from left to right: differentially expressed genes (DEGs); TCR sequence logos showing the V and J gene usage and CDR3 sequences for the TCR alpha and beta chains; biased TCR sequence scores, with red indicating elevated scores and blue indicating decreased scores relative to the rest of the dataset (see CoNGA manuscript Table S3 for score definitions); GEX 'logos' for each cluster consisting of a panel of marker genes shown with red disks colored by mean expression and sized according to the fraction of cells expressing the gene (gene names are given above).

DEG and TCRseq sequence logos are scaled by the adjusted P value of the associations, with full logo height requiring a top adjusted P value below 10-6. DEGs with fold-change less than 2 are shown in gray. Each cluster is indicated by a bicolored disk colored according to GEX cluster (left half) and TCR cluster (right half). The two numbers above each disk show the number of hits within the cluster (on the left) and the total number of cells in those clonotypes (on the right). The dendrogram at the left shows similarity relationships among the clusters based on connections in the GEX and TCR neighbor graphs.

The choice of which marker genes to use for the GEX umap panels and for the cluster GEX logos can be configured using run_conga.py command line flags or arguments to the conga.plotting.make_logo_plots function.
Image source: Rotelle_GIC_Final2_tcr_clumping_logos.png

tcr_db_match

This table stores significant matches between TCRs in adata and TCRs in the file /scratch.global/ben_testing/conga/conga/data/new_paired_tcr_db_for_matching_nr.tsv

P values of matches are assigned by turning the raw TCRdist score into a P value based on a model of the V(D)J rearrangement process, so matches between TCRs that are very far from germline (for example) are assigned a higher significance.

Columns:

tcrdist: TCRdist distance between the two TCRs (adata query and db hit)

pvalue_adj: raw P value of the match * num query TCRs * num db TCRs

fdr_value: Benjamini-Hochberg FDR value for match

clone_index: index within adata of the query TCR clonotype

db_index: index of the hit in the database being matched

va,ja,cdr3a,vb,jb,cdr3b

db_XXX: where XXX is a field in the literature database

tcr_graph_vs_gex_features

This table has results from a graph-vs-features analysis in which we look for genes that are differentially expressed (elevated) in specific neighborhoods of the TCR neighbor graph. Differential expression is assessed by a ttest first, for speed, and then by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value passes an initial threshold (default is 10* the pvalue threshold).

Each row of the table represents a single significant association, in other words a neighborhood (defined by the central clonotype index) and a gene.

The columns are as follows:

ttest_pvalue_adj= ttest_pvalue * number of comparisons mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons log2enr = log2 fold change of gene in neighborhood (will be positive) gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores num_fg= the number of clonotypes in the neighborhood (including center) mean_fg= the mean value of the feature in the neighborhood mean_bg= the mean value of the feature outside the neighborhood feature= the name of the gene mait_fraction= the fraction of the skewed clonotypes that have an invariant TCR clone_index= the index in the anndata dataset of the clonotype that is the center of the neighborhood.

ttest_pvalue_adj	mwu_pvalue_adj	log2enr	gex_cluster	tcr_cluster	feature	mean_fg	mean_bg	num_fg	clone_index	nbr_frac	graph_type	feature_type
3.637877e-13	1.259886e-78	8.876144	3	7	ENSMMUG00000054409	2.968077	0.038523	33	-1	0.00	tcr_cluster	gex
4.330276e-20	2.475967e-37	6.343509	2	8	ENSMMUG00000061119	2.803675	0.174741	30	-1	0.00	tcr_cluster	gex
6.740658e-03	4.197116e-35	6.343996	2	7	ENSMMUG00000054409	1.696959	0.053418	54	399	0.10	tcr_nbr	gex
3.616694e-02	2.214514e-31	5.810826	2	7	ENSMMUG00000054409	1.581101	0.066507	54	404	0.10	tcr_nbr	gex
5.524648e-02	3.436715e-29	5.899136	3	7	ENSMMUG00000054409	1.601228	0.064233	54	402	0.10	tcr_nbr	gex
1.564020e-01	1.070536e-28	5.546289	2	7	ENSMMUG00000054409	1.518759	0.073550	54	419	0.10	tcr_nbr	gex
1.117727e-01	1.560612e-28	5.569513	2	7	ENSMMUG00000054409	1.524350	0.072918	54	421	0.10	tcr_nbr	gex
1.072842e-01	1.860159e-28	5.571641	2	7	ENSMMUG00000054409	1.524861	0.072860	54	422	0.10	tcr_nbr	gex
2.804220e-01	4.843464e-26	5.457238	2	7	ENSMMUG00000054409	1.497120	0.075994	54	417	0.10	tcr_nbr	gex
1.775188e-01	1.238556e-25	5.462943	2	7	ENSMMUG00000054409	1.498515	0.075837	54	407	0.10	tcr_nbr	gex
8.846428e-01	4.604450e-23	5.112633	2	7	ENSMMUG00000054409	1.410601	0.085768	54	408	0.10	tcr_nbr	gex
9.328553e-01	1.026424e-22	5.057032	3	7	ENSMMUG00000054409	1.396264	0.087388	54	418	0.10	tcr_nbr	gex
1.309988e+00	5.989549e-21	5.132640	2	7	ENSMMUG00000054409	1.415736	0.085188	54	406	0.10	tcr_nbr	gex
1.481972e+00	1.612634e-20	5.029298	3	7	ENSMMUG00000054409	1.389076	0.088200	54	423	0.10	tcr_nbr	gex
2.931209e-04	3.823810e-19	2.501481	0	2	ENSMMUG00000061119	0.951813	0.247530	57	-1	0.00	tcr_cluster	gex
3.435755e+00	2.149080e-18	4.922413	2	7	ENSMMUG00000054409	1.361163	0.091353	54	414	0.10	tcr_nbr	gex
3.285024e+00	2.149080e-18	4.917222	2	7	ENSMMUG00000054409	1.359799	0.091507	54	403	0.10	tcr_nbr	gex
3.335224e+00	2.288763e-18	4.909072	2	7	ENSMMUG00000054409	1.357656	0.091750	54	405	0.10	tcr_nbr	gex
3.389983e+00	3.069146e-18	4.880029	2	7	ENSMMUG00000054409	1.350005	0.092614	54	397	0.10	tcr_nbr	gex
3.860440e+00	4.199074e-18	4.827127	3	7	ENSMMUG00000054409	1.336010	0.094195	54	398	0.10	tcr_nbr	gex
3.572116e+00	4.859018e-18	4.833613	2	7	ENSMMUG00000054409	1.337729	0.094001	54	427	0.10	tcr_nbr	gex
3.933236e+00	5.621568e-18	4.796497	3	7	ENSMMUG00000054409	1.327874	0.095114	54	425	0.10	tcr_nbr	gex
5.550704e+00	1.755062e-17	4.551553	3	7	ENSMMUG00000054409	1.262026	0.102553	54	411	0.10	tcr_nbr	gex
2.649942e-09	8.465841e-17	4.280124	2	7	ENSMMUG00000056515	3.054797	0.713226	54	313	0.10	tcr_nbr	gex
1.089627e-08	8.958174e-17	4.308333	2	4	ENSMMUG00000056515	3.070184	0.711488	54	212	0.10	tcr_nbr	gex
3.592379e-02	2.390806e-16	2.487117	0	2	ENSMMUG00000061119	0.956520	0.251418	54	187	0.10	tcr_nbr	gex
7.090872e+00	2.836648e-16	4.820641	3	7	ENSMMUG00000054409	1.334289	0.094389	54	410	0.10	tcr_nbr	gex
1.893355e-09	3.523686e-16	4.323484	2	7	ENSMMUG00000056515	3.078450	0.710554	54	109	0.10	tcr_nbr	gex
8.125980e-02	5.935875e-16	2.423377	0	2	ENSMMUG00000061119	0.935882	0.253750	54	177	0.10	tcr_nbr	gex
1.043029e-01	1.005052e-15	2.668576	1	2	ENSMMUG00000061119	1.016149	0.244682	54	200	0.10	tcr_nbr	gex
8.291229e-08	6.401231e-15	4.098499	2	7	ENSMMUG00000056515	2.955863	0.724403	54	412	0.10	tcr_nbr	gex
5.006807e-08	1.275900e-14	4.169137	2	7	ENSMMUG00000056515	2.994312	0.720059	54	277	0.10	tcr_nbr	gex
1.643447e-07	1.420431e-14	4.115502	2	4	ENSMMUG00000056515	2.965114	0.723357	54	222	0.10	tcr_nbr	gex
5.138232e-01	4.277048e-14	2.573013	0	2	ENSMMUG00000061119	0.984590	0.248247	54	162	0.10	tcr_nbr	gex
1.149504e+00	1.472213e-13	2.417194	0	2	ENSMMUG00000061119	0.933889	0.253975	54	179	0.10	tcr_nbr	gex
5.304837e-01	1.675102e-13	2.355310	0	2	ENSMMUG00000061119	0.914030	0.256218	54	160	0.10	tcr_nbr	gex
4.001114e-07	2.380009e-13	4.056406	2	4	ENSMMUG00000056515	2.932970	0.726989	54	55	0.10	tcr_nbr	gex
7.951065e-01	4.733059e-13	2.244093	0	2	ENSMMUG00000061119	0.878763	0.260203	54	196	0.10	tcr_nbr	gex
4.891390e-05	1.930714e-12	3.767220	2	4	ENSMMUG00000056515	2.776131	0.744707	54	320	0.10	tcr_nbr	gex
7.886987e+00	2.056620e-12	7.482114	3	7	ENSMMUG00000054409	3.600625	0.181684	6	399	0.01	tcr_nbr	gex
8.158782e+00	2.166197e-12	7.472014	3	7	ENSMMUG00000054409	3.594243	0.181757	6	397	0.01	tcr_nbr	gex
6.733624e+00	2.665200e-12	7.419899	3	7	ENSMMUG00000054409	3.561323	0.182133	6	412	0.01	tcr_nbr	gex
4.574165e+00	2.955696e-12	7.486300	3	7	ENSMMUG00000054409	3.603271	0.181654	6	402	0.01	tcr_nbr	gex
9.128151e+00	3.277424e-12	7.391793	3	7	ENSMMUG00000054409	3.543579	0.182335	6	415	0.01	tcr_nbr	gex
1.203081e+00	3.527318e-12	2.308465	1	2	ENSMMUG00000061119	0.899108	0.257904	54	184	0.10	tcr_nbr	gex
2.526534e+00	3.848063e-12	2.324406	0	2	ENSMMUG00000061119	0.904175	0.257332	54	193	0.10	tcr_nbr	gex
4.742955e-06	4.282523e-12	3.853640	0	7	ENSMMUG00000056515	2.822914	0.739422	54	413	0.10	tcr_nbr	gex
5.670211e-05	6.391235e-12	3.708465	2	7	ENSMMUG00000056515	2.744373	0.748295	54	126	0.10	tcr_nbr	gex
2.339934e-05	6.922410e-12	3.757844	2	7	ENSMMUG00000056515	2.771061	0.745280	54	28	0.10	tcr_nbr	gex
1.752553e-05	8.879416e-12	3.852103	2	4	ENSMMUG00000056515	2.822081	0.739516	54	415	0.10	tcr_nbr	gex

Omitted 82 lines

tcr_graph_vs_gex_features_plot

This plot summarizes the results of a graph versus features analysis by labeling the clonotypes at the center of each biased neighborhood with the name of the feature biased in that neighborhood. The feature names are drawn in colored boxes whose color is determined by the strength and direction of the feature score bias (from bright red for features that are strongly elevated to bright blue for features that are strongly decreased in the corresponding neighborhoods, relative to the rest of the dataset).

At most one feature (the top scoring) is shown for each clonotype (ie, neighborhood). The UMAP xy coordinates for this plot are stored in adata.obsm['X_tcr_2d']. The score used for ranking correlations is 'mwu_pvalue_adj'. The threshold score for displaying a feature is 1.0. The feature column is 'feature'. Since we also run graph-vs-features using "neighbor" graphs that are defined by clusters, ie where each clonotype is connected to all the other clonotypes in the same cluster, some biased features may be associated with a cluster rather than a specific clonotype. Those features are labeled with a '*' at the end and shown near the centroid of the clonotypes belonging to that cluster.
Image source: Rotelle_GIC_Final2_tcr_graph_vs_gex_features_plot.png

tcr_graph_vs_gex_features_panels

Graph-versus-feature analysis was used to identify a set of GEX features that showed biased distributions in TCR neighborhoods. This plot shows the distribution of the top-scoring GEX features on the TCR UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons). At most 3 features from clonotype neighbhorhoods in each (GEX,TCR) cluster pair are shown. The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel. Points are plotted in order of increasing feature score.
Image source: Rotelle_GIC_Final2_tcr_graph_vs_gex_features_panels.png

tcr_genes_vs_gex_features

ttest_pvalue_adj	mwu_pvalue_adj	log2enr	gex_cluster	tcr_cluster	feature	mean_fg	mean_bg	num_fg	clone_index	mait_fraction	gene_segment	graph_type	feature_type
7.484724e-15	8.969480e-92	11.094260	3	5	ENSMMUG00000049767	3.527550	0.015000	18	-1	0.0	TRBV5-8	tcr_genes	gex
1.055481e-18	5.106906e-84	9.171846	2	7	ENSMMUG00000054409	3.159566	0.038370	31	-1	0.0	TRAV6	tcr_genes	gex
8.999149e-17	1.240647e-79	10.937514	0	1	ENSMMUG00000063185	3.774666	0.021480	24	-1	0.0	TRBV4-2	tcr_genes	gex
4.632209e-13	1.034259e-64	9.338192	7	3	ENSMMUG00000062211	4.019811	0.081115	21	-1	0.0	TRBV12-2	tcr_genes	gex
2.928629e-01	2.430952e-63	8.472871	6	1	ENSMMUG00000056910	2.271786	0.024183	11	-1	0.0	TRAV16	tcr_genes	gex
6.316045e-13	2.839198e-51	8.579260	6	1	ENSMMUG00000060662	3.342130	0.068893	15	-1	0.0	TRAV8-7	tcr_genes	gex
1.107452e-12	9.851018e-46	8.352445	0	4	ENSMMUG00000062085	3.413647	0.086066	21	-1	0.2	TRBV4-3	tcr_genes	gex
1.855973e-02	1.242521e-39	9.308708	2	4	ENSMMUG00000059325	2.991692	0.029397	8	-1	0.0	TRAV25	tcr_genes	gex
8.302680e-06	1.467056e-37	6.595270	0	1	ENSMMUG00000057062	1.951733	0.060604	15	-1	0.0	TRAV8-3	tcr_genes	gex
1.226911e-19	7.015239e-37	6.343509	2	8	ENSMMUG00000061119	2.803675	0.174741	30	-1	0.0	TRAV18	tcr_genes	gex
2.178532e-106	1.600235e-36	5.592459	2	7	ENSMMUG00000056515	3.728990	0.610970	58	-1	0.0	TRBV6-3	tcr_genes	gex
1.344410e-10	1.066049e-35	7.692902	7	0	ENSMMUG00000043894	3.622388	0.162158	19	-1	0.0	TRBV20-1	tcr_genes	gex
3.968732e-01	3.184652e-34	5.313467	6	1	ENSMMUG00000061081	1.256408	0.061273	19	-1	0.0	TRAV8-2	tcr_genes	gex
6.087152e+00	5.246990e-34	8.162003	0	3	ENSMMUG00000061255	2.457652	0.036600	7	-1	0.0	TRBV5-6	tcr_genes	gex
3.710291e-10	5.752428e-29	7.097247	2	2	ENSMMUG00000051385	3.573801	0.225597	23	-1	0.0	TRBV7-6	tcr_genes	gex
9.155726e-05	2.140831e-26	7.509862	6	0	ENSMMUG00000062974	2.936639	0.093444	12	-1	0.0	TRAV13-2	tcr_genes	gex
7.397531e-03	3.309419e-23	7.249660	2	8	ENSMMUG00000062211	3.442710	0.181418	9	-1	0.0	TRBV12-3	tcr_genes	gex
3.152396e-05	3.535373e-22	2.727790	0	2	ENSMMUG00000061119	1.043334	0.244951	52	-1	0.0	TRAV19	tcr_genes	gex
1.739503e-02	1.019891e-21	7.777559	2	4	ENSMMUG00000065017	3.209041	0.102794	9	-1	0.0	TRAV12-1	tcr_genes	gex
1.221002e-34	8.738056e-17	5.363096	2	4	ENSMMUG00000056515	3.915709	0.786193	28	-1	0.0	TRBV6-2	tcr_genes	gex
2.784245e-02	6.241326e-12	6.818597	2	1	ENSMMUG00000043894	3.442513	0.237543	8	-1	0.0	TRBV21-1	tcr_genes	gex
7.080497e-03	9.877314e-07	6.670205	2	10	ENSMMUG00000051385	3.695223	0.326019	7	-1	0.0	TRBV7-4	tcr_genes	gex
1.119380e-01	7.839223e-05	4.851182	4	10	ENSMMUG00000051385	2.545002	0.341355	7	-1	0.0	TRBV5-6	tcr_genes	gex
3.726081e-06	7.382818e-04	4.167548	2	1	ENSMMUG00000056515	3.269982	0.878995	16	-1	0.0	TRBV10-2	tcr_genes	gex
1.901853e-08	1.002423e-03	2.294030	4	5	ENSMMUG00000056515	2.074884	0.883734	30	-1	0.0	TRBV9	tcr_genes	gex
5.107602e+00	1.005481e-03	6.362424	0	5	ENSMMUG00000043894	3.249662	0.263284	4	-1	0.0	TRBV19	tcr_genes	gex
8.124517e-01	4.614008e-02	1.227987	5	4	WASHC3	0.765917	0.399690	64	-1	0.0	TRBJ2-4	tcr_genes	gex
4.676707e+00	7.089933e-02	2.693193	7	9	MAP2K3	1.100824	0.270232	9	-1	0.0	TRBV6-1	tcr_genes	gex
3.887516e-77	4.397661e-01	7.171084	3	2	ENSMMUG00000051385	4.114374	0.349118	3	-1	0.0	TRBV7-7	tcr_genes	gex
4.484605e-01	2.270749e+00	0.888811	0	0	SLA	1.824650	1.337273	56	-1	0.0	TRBJ2-3	tcr_genes	gex
7.139158e-01	3.073687e+00	3.521512	7	1	TMEM135	0.964564	0.132244	3	-1	0.0	TRAV8-4	tcr_genes	gex
8.406671e-01	8.569616e+00	3.399464	7	1	CSTF3	0.964564	0.143120	3	-1	0.0	TRAV8-4	tcr_genes	gex

tcr_genes_vs_gex_features_panels

gex_graph_vs_tcr_features

This table has results from a graph-vs-features analysis in which we look at the distribution of a set of TCR-defined features over the GEX neighbor graph. We look for neighborhoods in the graph that have biased score distributions, as assessed by a ttest first, for speed, and then by a mannwhitneyu test for nbrhood/score combinations whose ttest P-value passes an initial threshold (default is 10* the pvalue threshold).

Each row of the table represents a single significant association, in other words a neighborhood (defined by the central clonotype index) and a tcr feature.

The columns are as follows:

ttest_pvalue_adj= ttest_pvalue * number of comparisons ttest_stat= ttest statistic (sign indicates where feature is up or down) mwu_pvalue_adj= mannwhitney-U P-value * number of comparisons gex_cluster= the consensus GEX cluster of the clonotypes w/ biased scores tcr_cluster= the consensus TCR cluster of the clonotypes w/ biased scores num_fg= the number of clonotypes in the neighborhood (including center) mean_fg= the mean value of the feature in the neighborhood mean_bg= the mean value of the feature outside the neighborhood feature= the name of the TCR score mait_fraction= the fraction of the skewed clonotypes that have an invariant TCR clone_index= the index in the anndata dataset of the clonotype that is the center of the neighborhood.

ttest_pvalue_adj	ttest_stat	mwu_pvalue_adj	gex_cluster	tcr_cluster	num_fg	mean_fg	mean_bg	feature	mait_fraction	clone_index	nbr_frac	graph_type	feature_type
3.636894e-27	2.435638e+06	1.562678e-112	4	9	6	1.000000	0.000000	mait	1.000000	12	0.01	gex_nbr	tcr
0.000000e+00	1.845495e+02	9.519093e-46	4	9	6	1.000000	0.015209	TRAV1-2	1.000000	12	0.01	gex_nbr	tcr
3.867305e-01	-4.951298e+00	2.348437e-01	2	0	54	0.506821	0.795354	af4	0.000000	26	0.10	gex_nbr	tcr
9.933085e-02	-4.471693e+00	4.333296e-01	7	0	29	-0.126722	0.222531	cd8	0.000000	-1	0.00	gex_cluster	tcr
2.098956e-01	-5.082872e+00	7.249505e-01	2	0	54	0.523511	0.793468	af4	0.153846	12	0.10	gex_nbr	tcr
1.007617e+00	3.463887e+00	9.733440e-01	4	9	60	-5.399413	-5.587273	mjenergy	0.266667	-1	0.00	gex_cluster	tcr
4.460173e-01	3.724043e+00	9.859175e-01	4	5	60	0.720707	0.700891	nndists_tcr	0.066667	-1	0.00	gex_cluster	tcr
4.178701e-02	-4.250926e+00	3.201596e+00	3	6	78	0.064103	0.207048	TRBJ2-1	0.000000	-1	0.00	gex_cluster	tcr
1.389785e-11	-7.971102e+00	5.620059e+00	4	6	60	0.000000	0.118644	TRBJ2-3	0.000000	-1	0.00	gex_cluster	tcr

gex_graph_vs_tcr_features_plot

This plot summarizes the results of a graph versus features analysis by labeling the clonotypes at the center of each biased neighborhood with the name of the feature biased in that neighborhood. The feature names are drawn in colored boxes whose color is determined by the strength and direction of the feature score bias (from bright red for features that are strongly elevated to bright blue for features that are strongly decreased in the corresponding neighborhoods, relative to the rest of the dataset).

At most one feature (the top scoring) is shown for each clonotype (ie, neighborhood). The UMAP xy coordinates for this plot are stored in adata.obsm['X_gex_2d']. The score used for ranking correlations is 'mwu_pvalue_adj'. The threshold score for displaying a feature is 1.0. The feature column is 'feature'. Since we also run graph-vs-features using "neighbor" graphs that are defined by clusters, ie where each clonotype is connected to all the other clonotypes in the same cluster, some biased features may be associated with a cluster rather than a specific clonotype. Those features are labeled with a '*' at the end and shown near the centroid of the clonotypes belonging to that cluster.
Image source: Rotelle_GIC_Final2_gex_graph_vs_tcr_features_plot.png

gex_graph_vs_tcr_features_panels

Graph-versus-feature analysis was used to identify a set of TCR features that showed biased distributions in GEX neighborhoods. This plot shows the distribution of the top-scoring TCR features on the GEX UMAP 2D landscape. The features are ranked by 'mwu_pvalue_adj' ie Mann-Whitney-Wilcoxon adjusted P value (raw P value * number of comparisons). At most 3 features from clonotype neighbhorhoods in each (GEX,TCR) cluster pair are shown. The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel. Points are plotted in order of increasing feature score.
Image source: Rotelle_GIC_Final2_gex_graph_vs_tcr_features_panels.png

graph_vs_features_gex_clustermap

This plot shows the distribution of significant features from graph-vs-features or HotSpot analysis plotted across the GEX landscape. Rows are features and columns are individual clonotypes. Columns are ordered by hierarchical clustering (if a dendrogram is present above the heatmap) or by a 1D UMAP projection (used for very large datasets or if 'X_pca_gex' is not present in adata.obsm_keys()). Rows are ordered by hierarchical clustering with a correlation metric.

The row colors to the left of the heatmap show the feature type (blue=TCR, orange=GEX). The row colors to the left of those indicate the strength of the graph-vs-feature correlation (also included in the feature labels to the right of the heatmap; keep in mind that highly significant P values for some features may shift the colorscale so everything else looks dark blue).

The column colors above the heatmap are GEX clusters (and TCR V/J genes if plotting against the TCR landscape). The text above the column colors provides more info.

Feature scores are Z-score normalized and then averaged over the K=53 nearest neighbors (0 means no nbr-averaging).

The 'coolwarm' colormap is centered at Z=0.

Since features of the same type (GEX or TCR) as the landscape and neighbor graph (ie GEX features) are more highly correlated over graph neighborhoods, their neighbor-averaged scores will show more extreme variation. For this reason, the nbr-averaged scores for these features from the same modality as the landscape itself are downscaled by a factor of rescale_factor_for_self_features=0.33.

The colormap in the top left is for the Z-score normalized, neighbor-averaged scores (multiply by 3.03 to get the color scores for the GEX features).

Image source: Rotelle_GIC_Final2_graph_vs_features_gex_clustermap.png

graph_vs_features_tcr_clustermap

This plot shows the distribution of significant features from graph-vs-features or HotSpot analysis plotted across the TCR landscape. Rows are features and columns are individual clonotypes. Columns are ordered by hierarchical clustering (if a dendrogram is present above the heatmap) or by a 1D UMAP projection (used for very large datasets or if 'X_pca_tcr' is not present in adata.obsm_keys()). Rows are ordered by hierarchical clustering with a correlation metric.

The row colors to the left of the heatmap show the feature type (blue=TCR, orange=GEX). The row colors to the left of those indicate the strength of the graph-vs-feature correlation (also included in the feature labels to the right of the heatmap; keep in mind that highly significant P values for some features may shift the colorscale so everything else looks dark blue).

The column colors above the heatmap are TCR clusters (and TCR V/J genes if plotting against the TCR landscape). The text above the column colors provides more info.

Feature scores are Z-score normalized and then averaged over the K=53 nearest neighbors (0 means no nbr-averaging).

The 'coolwarm' colormap is centered at Z=0.

Since features of the same type (GEX or TCR) as the landscape and neighbor graph (ie TCR features) are more highly correlated over graph neighborhoods, their neighbor-averaged scores will show more extreme variation. For this reason, the nbr-averaged scores for these features from the same modality as the landscape itself are downscaled by a factor of rescale_factor_for_self_features=0.33.

The colormap in the top left is for the Z-score normalized, neighbor-averaged scores (multiply by 3.03 to get the color scores for the TCR features).

Image source: Rotelle_GIC_Final2_graph_vs_features_tcr_clustermap.png

graph_vs_summary

Summary figure for the graph-vs-graph and graph-vs-features analyses.
Image source: Rotelle_GIC_Final2_graph_vs_summary.png

gex_clusters_tcrdist_trees

These are TCRdist hierarchical clustering trees for the GEX clusters (cluster assignments stored in adata.obs['clusters_gex']). The trees are colored by CoNGA score with a color score range of 5.32e+00 (blue) to 5.32e-09 (red). For coloring, CoNGA scores are log-transformed, negated, and square-rooted (with an offset in there, too, roughly speaking).
Image source: Rotelle_GIC_Final2_gex_clusters_tcrdist_trees.png

conga_threshold_tcrdist_tree

This is a TCRdist hierarchical clustering tree for the clonotypes with CoNGA score less than 10.0. The tree is colored by CoNGA score with a color score range of 1.00e+01 (blue) to 1.00e-08 (red). For coloring, CoNGA scores are log-transformed, negated, and square-rooted (with an offset in there, too, roughly speaking).
Image source: Rotelle_GIC_Final2_conga_threshold_tcrdist_tree.png

hotspot_features

Find GEX (TCR) features that show a biased distribution across the TCR (GEX) neighbor graph, using a simplified version of the Hotspot method from the Yosef lab.

DeTomaso, D., & Yosef, N. (2021). "Hotspot identifies informative gene modules across modalities of single-cell genomics." Cell Systems, 12(5), 446–456.e9.

PMID:33951459

Columns:

Z: HotSpot Z statistic

pvalue_adj: Raw P value times the number of tests (crude Bonferroni correction)

nbr_frac: The K NN nbr fraction used for the neighbor graph construction (nbr_frac = 0.1 means K=0.1*num_clonotypes neighbors)

Z	pvalue_adj	feature	feature_type	nbr_frac
49.336595	0.000000e+00	ENSMMUG00000056515	gex	0.10
40.232142	0.000000e+00	ENSMMUG00000054409	gex	0.10
37.780389	0.000000e+00	ENSMMUG00000061119	gex	0.10
30.231293	6.114312e-197	ENSMMUG00000054409	gex	0.01
23.005884	2.707485e-113	ENSMMUG00000061119	gex	0.01
20.949730	1.255227e-93	ENSMMUG00000056515	gex	0.01
19.998144	3.802338e-85	ENSMMUG00000062211	gex	0.10
19.768175	4.393179e-85	mait	tcr	0.01
18.625673	1.323592e-73	ENSMMUG00000063185	gex	0.10
16.644333	2.212818e-58	ENSMMUG00000051385	gex	0.10
16.490307	2.865384e-57	ENSMMUG00000049767	gex	0.10
16.440923	6.480665e-57	ENSMMUG00000043894	gex	0.10
15.019460	3.642073e-47	RORC	gex	0.01
14.974161	7.205824e-47	ENSMMUG00000062085	gex	0.10
13.580694	3.467705e-38	ENSMMUG00000063185	gex	0.01
12.154972	3.590778e-30	ENSMMUG00000062211	gex	0.01
12.041434	1.431390e-29	ENSMMUG00000043894	gex	0.01
11.386613	3.243373e-26	ENSMMUG00000057062	gex	0.10
11.078364	1.062752e-24	ENSMMUG00000059325	gex	0.10
11.061355	1.284877e-24	ENSMMUG00000060662	gex	0.10
10.571318	2.692498e-22	BLK	gex	0.01
10.533641	4.021138e-22	ENSMMUG00000057062	gex	0.01
10.423756	1.284975e-21	ENSMMUG00000051385	gex	0.01
9.397822	3.705435e-17	ENSMMUG00000059234	gex	0.01
8.959303	2.173455e-15	ENSMMUG00000062085	gex	0.01
8.951750	2.327481e-15	ENSMMUG00000060662	gex	0.01
8.771732	1.170346e-14	KLRB1	gex	0.01
8.690750	2.395083e-14	ENSMMUG00000065017	gex	0.01
8.649237	3.448732e-14	ENSMMUG00000061255	gex	0.10
8.565631	7.149958e-14	TYROBP	gex	0.01
8.352788	4.434904e-13	ENSMMUG00000049767	gex	0.01
7.703842	1.036472e-12	TRAV1-2	tcr	0.01
7.995739	8.567680e-12	ENSMMUG00000061255	gex	0.01
7.391101	9.686542e-10	ENSMMUG00000061081	gex	0.10
7.316706	1.690483e-09	ENSMMUG00000052673	gex	0.10
7.273446	2.331063e-09	ENSMMUG00000056431	gex	0.10
7.221398	3.422829e-09	ENSMMUG00000061499	gex	0.01
7.077887	9.736488e-09	STAP1	gex	0.01
6.457199	7.094916e-07	ENSMMUG00000016687	gex	0.01
5.719503	8.386610e-07	mait	tcr	0.10
6.393141	1.081032e-06	KNTC1	gex	0.01
6.348860	1.442928e-06	ENSMMUG00000065017	gex	0.10
5.406902	5.033755e-06	TRAV12-1	tcr	0.01
6.007525	1.253080e-05	ENSMMUG00000062974	gex	0.10
5.910594	2.267504e-05	ENSMMUG00000059325	gex	0.01
5.892373	2.532342e-05	C1H1orf53	gex	0.01
5.764445	5.449768e-05	ENSMMUG00000049338	gex	0.01
5.762043	5.527917e-05	ENSMMUG00000056431	gex	0.01
5.467192	3.041440e-04	ADA2	gex	0.01
5.392620	4.618999e-04	ENSMMUG00000056910	gex	0.10

Omitted 15 lines

hotspot_gex_umap

HotSpot analysis (Nir Yosef lab, PMID: 33951459) was used to identify a set of GEX (TCR) features that showed biased distributions in TCR (GEX) space. This plot shows the distribution of the top-scoring HotSpot features on the GEX UMAP 2D landscape. The features are ranked by adjusted P value (raw P value * number of comparisons). The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel.

Features are filtered based on correlation coefficient to reduce redundancy: if a feature has a correlation of >= 0.9 (the max_feature_correlation argument to conga.plotting.plot_hotspot_umap) to a previously plotted feature, that feature is skipped. Points are plotted in order of increasing feature score
Image source: Rotelle_GIC_Final2_hotspot_combo_features_0.100_nbrs_gex_plot_umap_nbr_avg.png

hotspot_gex_clustermap

hotspot_tcr_umap

HotSpot analysis (Nir Yosef lab, PMID: 33951459) was used to identify a set of GEX (TCR) features that showed biased distributions in TCR (GEX) space. This plot shows the distribution of the top-scoring HotSpot features on the TCR UMAP 2D landscape. The features are ranked by adjusted P value (raw P value * number of comparisons). The raw scores for each feature are averaged over the K nearest neighbors (K is indicated in the lower right corner of each panel) for each clonotype. The min and max nbr-averaged scores are shown in the upper corners of each panel.

Features are filtered based on correlation coefficient to reduce redundancy: if a feature has a correlation of >= 0.9 (the max_feature_correlation argument to conga.plotting.plot_hotspot_umap) to a previously plotted feature, that feature is skipped. Points are plotted in order of increasing feature score
Image source: Rotelle_GIC_Final2_hotspot_combo_features_0.100_nbrs_tcr_plot_umap_nbr_avg.png